gpt-5.6-sol
nano-gpt-data-curation — graded by the task's verifier against a measured baseline.
- backend
- modal
- variant
- codex azure_ai/gpt-5.6-sol
- metric
- held-out multi-domain perplexity
- actions
- 285
- duration
- 1h 22m
- recorded
- 2026-08-04
run iddclm-nano-curation__NqS7udZ
Everything gpt-5.6-sol did on this task, in order.
download JSON ↗encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({session_id:20659,chars:\"\",yield_time_ms:30000,max_output_tokens:10000}); text(r);\n"
}exec result
Script running with cell ID 80
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "80",
"yield_time_ms": 30000,
"max_tokens": 10000
}wait result
Script completed
Wall time 0.0 seconds
Output:
{"chunk_id":"e2874e","wall_time_seconds":12.516482108,"exit_code":0,"original_token_count":67,"output":"{'losses': [6.775870448253194, 5.7054926450135275, 5.74644995517418, 5.275234879040327], 'ppls': [876.4419284450734, 300.51349005978784, 313.07724686095503, 195.43637503025207], 'mean_loss': 5.875761981870307, 'ppl': 356.29604839072255, 'train_s': 55.0595486164093}\n"}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({cmd:\"python - <<'PY'\\nimport json,numpy as np\\nD=np.load('work/domain_scores2.npy').argmax(1)\\nfor f in ['neural_equal','neural_mix','neural_wiki']:\\n ids=json.load(open('work/'+f+'.json'))[:15000]\\n print(f,len(ids),sum(i>=114000 for i in ids),np.bincount(D[ids],minlength=4))\\nPY\\ncat .timer/remaining_secs\",workdir:\"/workspace\",yield_time_ms:10000,max_output_tokens:1000}); text(r);\n"
}exec result
Script completed
Wall time 0.3 seconds
Output:
{"chunk_id":"931bf5","wall_time_seconds":0.14833718,"exit_code":0,"original_token_count":35,"output":"neural_equal 15000 1139 [4222 3171 5224 2383]\nneural_mix 15000 1184 [4815 3116 4622 2447]\nneural_wiki 15000 930 [6657 2385 4061 1897]\n3477\n"}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({cmd:\"python - <<'PY'\\nimport json\\nx=json.load(open('work/neural_equal.json'));json.dump([i for i in x if i<114000],open('work/neural_early.json','w'))\\nPY\\npython work/pack_fast.py data/pool.jsonl work/neural_early.json work/neural_early.npy && PYTHONPATH=. python work/train_diag.py --train_npy work/neural_early.npy --out_json work/neural_early_result.json\",workdir:\"/workspace\",yield_time_ms:1000,max_output_tokens:10000}); text(r);\n"
}exec result
Script completed
Wall time 1.2 seconds
Output:
{"chunk_id":"0ecece","wall_time_seconds":1.001434255,"session_id":42015,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const patch = \"*** Begin Patch\\n*** Add File: /workspace/work/generic_score.py\\n+\\\"\\\"\\\"Small generic-web LM reference for Moore-Lewis contrastive scoring.\\\"\\\"\\\"\\n+import json,math,numpy as np,torch\\n+import torch.nn.functional as F\\n+from transformers import GPT2TokenizerFast\\n+from model import GPT,GPTConfig\\n+torch.manual_seed(2027);np.random.seed(2027);rng=np.random.default_rng(2027)\\n+tr=torch.from_numpy(np.load('work/random_all.npy').astype(np.int64))\\n+m=GPT(GPTConfig(block_size=128,vocab_size=50257,n_layer=4,n_head=4,n_embd=256,dropout=0,bias=False)).cuda().train()\\n+o=m.configure_optimizers(.1,7e-4,(.9,.95),'cuda')\\n+for it in range(1400):\\n+ ix=rng.integers(0,len(tr)-129,size=64);x=torch.stack([tr[i:i+128] for i in ix]).cuda();y=torch.stack([tr[i+1:i+129] for i in ix]).cuda()\\n+ lr=7e-4*(it+1)/101 if it<100 else 7e-5+.5*(1+math.cos(math.pi*(it-100)/1300))*6.3e-4\\n+ for g in o.param_groups:g['lr']=lr\\n+ with torch.autocast('cuda',dtype=torch.bfloat16):_,l=m(x,y)\\n+ o.zero_grad(set_to_none=True);l.backward();o.step()\\n+ if it%350==0:print('train',it,float(l))\\n+tok=GPT2TokenizerFast.from_pretrained('gpt2',local_files_only=True);tok.pad_token=tok.eos_token\\n+score=np.empty(182016,np.float32);batch=[];ids=[];m.eval()\\n+@torch.no_grad()\\n+def flush():\\n+ if not batch:return\\n+ z=tok(batch,add_special_tokens=False,truncation=True,max_length=129,padding='max_length',return_attention_mask=True,return_tensors='pt')\\n+ x=z.input_ids[:,:128].cuda();y=z.input_ids[:,1:129].cuda();mask=z.attention_mask[:,1:129].cuda();mask[:,:7]=0\\n+ with torch.autocast('cuda',dtype=torch.bfloat16):logits,_=m(x)\\n+ ce=F.cross_entropy(logits.float().reshape(-1,50257),y.reshape(-1),reduction='none').view(len(batch),128)\\n+ score[ids]=((ce*mask).sum(1)/mask.sum(1).clamp_min(1)).cpu().numpy();batch.clear();ids.clear()\\n+for line in open('data/pool.jsonl'):\\n+ r=json.loads(line);ids.append(r['id']);batch.append(r['text'])\\n+ if len(batch)>=256:flush()\\n+flush();np.save('work/generic_scores.npy',score);print(np.quantile(score,[0,.01,.1,.5,.9,.99,1]))\\n*** End Patch\";\nconst a = await tools.apply_patch(patch);\nconst r = await tools.exec_command({cmd:\"PYTHONPATH=. python work/generic_score.py\",workdir:\"/workspace\",yield_time_ms:1000,max_output_tokens:10000});\ntext(a); text(r);\n"
}exec result
Script completed
Wall time 1.2 seconds
Output:
{}{"chunk_id":"96edb8","wall_time_seconds":1.002130161,"session_id":49869,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({session_id:42015,chars:\"\",yield_time_ms:30000,max_output_tokens:10000}); text(r);\n"
}exec result
Script running with cell ID 84
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "84",
"yield_time_ms": 30000,
"max_tokens": 10000
}wait result
Script completed
Wall time 13.6 seconds
Output:
{"chunk_id":"6b08d5","wall_time_seconds":30.001743953,"session_id":42015,"original_token_count":57,"output":"Token indices sequence length is longer than the specified maximum sequence length for this model (1043 > 1024). Running this sequence through the model will result in indexing errors\npacked 12000000 tokens from 16931 documents\n"}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({cmd:\"nvidia-smi --query-compute-apps=pid,used_memory --format=csv,noheader; ps -o pid,etime,pcpu,args -C python\",workdir:\"/workspace\",yield_time_ms:10000,max_output_tokens:2000}); text(r);\n"
}exec result
Script completed
Wall time 0.2 seconds
Output:
{"chunk_id":"84f6f6","wall_time_seconds":0.021195443,"exit_code":0,"original_token_count":59,"output":"1, 34324 MiB\n1, 34324 MiB\n PID ELAPSED %CPU COMMAND\n 3809 01:05 47.2 python work/train_diag.py --train_npy work/neural_early.npy --out_json work/neural_early_result.json\n 3845 00:53 97.9 python work/generic_score.py\n"}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({session_id:42015,chars:\"\",yield_time_ms:30000,max_output_tokens:10000}); text(r);\n"
}exec result
Script running with cell ID 86
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "86",
"yield_time_ms": 30000,
"max_tokens": 10000
}wait result
Script completed
Wall time 11.3 seconds
Output:
{"chunk_id":"172d31","wall_time_seconds":27.739974272,"exit_code":0,"original_token_count":67,"output":"{'losses': [6.605582690629803, 5.618970886605685, 5.594917453703333, 6.22285978911353], 'ppls': [739.2104747616966, 275.60560781873187, 269.0554396454433, 504.14291486397747], 'mean_loss': 6.010582705013087, 'ppl': 407.72083204030247, 'train_s': 59.68716382980347}\n"}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({session_id:49869,chars:\"\",yield_time_ms:30000,max_output_tokens:10000}); text(r);\n"
}exec result
Script running with cell ID 87
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "87",
"yield_time_ms": 30000,
"max_tokens": 10000
}wait result
Script completed
Wall time 16.3 seconds
Output:
{"chunk_id":"46c99b","wall_time_seconds":30.002292096,"session_id":49869,"original_token_count":80,"output":"/workspace/work/generic_score.py:16: UserWarning: Converting a tensor with requires_grad=True to a scalar may lead to unexpected behavior.\nConsider using tensor.detach() first. (Triggered internally at /pytorch/torch/csrc/autograd/generated/python_variable_methods.cpp:835.)\n if it%350==0:print('train',it,float(l))\n"}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({session_id:49869,chars:\"\",yield_time_ms:30000,max_output_tokens:10000}); text(r);\n"
}exec result
Script running with cell ID 88
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "88",
"yield_time_ms": 30000,
"max_tokens": 10000
}wait result
Script completed
Wall time 14.4 seconds
Output:
{"chunk_id":"cef9da","wall_time_seconds":30.001522707,"session_id":49869,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({session_id:49869,chars:\"\",yield_time_ms:30000,max_output_tokens:10000}); text(r);\n"
}exec result
Script running with cell ID 89
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "89",
"yield_time_ms": 30000,
"max_tokens": 10000
}wait result
Script completed
Wall time 12.9 seconds
Output:
{"chunk_id":"4353bf","wall_time_seconds":30.002156932,"session_id":49869,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({cmd:\"ps -o pid,etime,pcpu,rss,args -C python; nvidia-smi --query-gpu=utilization.gpu,memory.used --format=csv,noheader; cat .timer/remaining_secs\",workdir:\"/workspace\",yield_time_ms:10000,max_output_tokens:1000}); text(r);\n"
}exec result
Script completed
Wall time 0.1 seconds
Output:
{"chunk_id":"373106","wall_time_seconds":0.000005037,"exit_code":0,"original_token_count":30,"output":" PID ELAPSED %CPU RSS COMMAND\n 3845 03:28 95.7 5405844 python work/generic_score.py\n0 %, 24805 MiB\n3257\n"}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({session_id:49869,chars:\"\",yield_time_ms:30000,max_output_tokens:10000}); text(r);\n"
}exec result
Script running with cell ID 91
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "91",
"yield_time_ms": 30000,
"max_tokens": 10000
}wait result
Script completed
Wall time 6.4 seconds
Output:
{"chunk_id":"dd120d","wall_time_seconds":30.0013251,"session_id":49869,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({session_id:49869,chars:\"\",yield_time_ms:30000,max_output_tokens:10000}); text(r);\n"
}exec result
Script running with cell ID 92
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "92",
"yield_time_ms": 30000,
"max_tokens": 10000
}wait result
Script completed
Wall time 9.6 seconds
Output:
{"chunk_id":"40cf38","wall_time_seconds":30.001840037,"session_id":49869,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({session_id:49869,chars:\"\",yield_time_ms:30000,max_output_tokens:10000}); text(r);\n"
}exec result
Script running with cell ID 93
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "93",
"yield_time_ms": 30000,
"max_tokens": 10000
}wait result
Script completed
Wall time 13.9 seconds
Output:
{"chunk_id":"120f0b","wall_time_seconds":30.001413277,"session_id":49869,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({session_id:49869,chars:\"\",yield_time_ms:30000,max_output_tokens:10000}); text(r);\n"
}exec result
Script running with cell ID 94
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "94",
"yield_time_ms": 30000,
"max_tokens": 10000
}wait result
Script completed
Wall time 5.8 seconds
Output:
{"chunk_id":"1a00ec","wall_time_seconds":30.001612647,"session_id":49869,"original_token_count":0,"output":""}